

BURGEON IT SERVICES
Data Scientist / AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist / AI Engineer with a 12-month contract, US remote location, offering competitive pay. Key skills include Knowledge Graphs, LLMs, MLOps, and advanced Machine Learning. A PhD or Master’s in a related field is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
March 10, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Texas, United States
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🧠 - Skills detailed
#Supervised Learning #Transformers #Langchain #Monitoring #NLP (Natural Language Processing) #Predictive Modeling #Cloud #MLflow #Neo4J #Python #ML (Machine Learning) #Unsupervised Learning #Scala #Databases #AI (Artificial Intelligence) #Data Science #Knowledge Graph #PyTorch #TensorFlow #Docker #Airflow #Deployment #RDF (Resource Description Framework) #"ETL (Extract #Transform #Load)" #Data Ingestion #Classification
Role description
Job Title: Data Scientist / AI Engineer
Work Location : : US Remote
Contract duration: 12
We’re looking for a few Senior Data Scientist / AI Engineer with deep expertise in Knowledge Graphs, Large Language Models (LLMs), and advanced Machine Learning.
This role is ideal for someone who enjoys solving complex problems, building intelligent systems end to end, and driving measurable impact in data rich environments.
What You’ll Do:
- Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning.
- Own end to end MLOps pipelines: data ingestion, training, deployment, monitoring, CI/CD.
- Collaborate with engineering, product, and domain teams to deliver production ready AI solutions.
- Build and scale Knowledge Graph–driven AI systems (ontology design, graph embeddings, reasoning).
- Develop and fine tune LLMs for classification, summarization, RAG, and agentic workflows.
What We’re Looking For:
- PhD (preferred) or Master’s in CS, AI, ML, Data Science, or related fields.
Strong hands on experience with:
- Core ML & Stats (optimization, supervised/unsupervised learning)
- NLP (semantic search, embeddings, text modeling)
- MLOps (MLflow, Kubeflow, Airflow, Docker, CI/CD)
- Proficiency in Python, PyTorch/TensorFlow, HuggingFace, LangChain, and cloud platforms.
- Ability to translate complex ideas into scalable, real world systems.
- Knowledge Graphs (RDF/OWL, Neo4j, graph ML)
- LLMs & Transformers (fine tuning, RAG, prompt engineering)
Preferred
- Healthcare insurance / Managed Care (MCO) experience — familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus.
- Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems.
- Background in explainable or responsible AI.
Job Title: Data Scientist / AI Engineer
Work Location : : US Remote
Contract duration: 12
We’re looking for a few Senior Data Scientist / AI Engineer with deep expertise in Knowledge Graphs, Large Language Models (LLMs), and advanced Machine Learning.
This role is ideal for someone who enjoys solving complex problems, building intelligent systems end to end, and driving measurable impact in data rich environments.
What You’ll Do:
- Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning.
- Own end to end MLOps pipelines: data ingestion, training, deployment, monitoring, CI/CD.
- Collaborate with engineering, product, and domain teams to deliver production ready AI solutions.
- Build and scale Knowledge Graph–driven AI systems (ontology design, graph embeddings, reasoning).
- Develop and fine tune LLMs for classification, summarization, RAG, and agentic workflows.
What We’re Looking For:
- PhD (preferred) or Master’s in CS, AI, ML, Data Science, or related fields.
Strong hands on experience with:
- Core ML & Stats (optimization, supervised/unsupervised learning)
- NLP (semantic search, embeddings, text modeling)
- MLOps (MLflow, Kubeflow, Airflow, Docker, CI/CD)
- Proficiency in Python, PyTorch/TensorFlow, HuggingFace, LangChain, and cloud platforms.
- Ability to translate complex ideas into scalable, real world systems.
- Knowledge Graphs (RDF/OWL, Neo4j, graph ML)
- LLMs & Transformers (fine tuning, RAG, prompt engineering)
Preferred
- Healthcare insurance / Managed Care (MCO) experience — familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus.
- Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems.
- Background in explainable or responsible AI.





